Alpha-Band Phase Modulates Bottom-up Feature Processing

Interdependence of "What" and "When" in the Brain

From a brain's-eye-view, when a stimulus occurs and what it is are interrelated aspects of interpreting the perceptual world. Yet in practice, the putative perceptual inferences about sensory content and timing are often dichotomized and not investigated as an integrated process. We here argue that neural temporal dynamics can influence what is perceived, and in turn, stimulus content can influence the time at which perception is achieved. This computational principle results from the highly interdependent relationship of what and when in the environment. Both brain processes and perceptual events display strong temporal variability that is not always modeled; we argue that understanding-and, minimally, modeling-this temporal variability is key for theories of how the brain generates unified and consistent neural representations and that we ignore temporal variability in our analysis practice at the peril of both data interpretation and theory-building. Here, we review what and when interactions in the brain, demonstrate via simulations how temporal variability can result in misguided interpretations and conclusions, and outline how to integrate and synthesize what and when in theories and models of brain computation.

Developmental alterations in the neural oscillatory dynamics underlying attentional reorienting

The neural and cognitive processes underlying the flexible allocation of attention undergo a protracted developmental course with changes occurring throughout adolescence. Despite documented age-related improvements in attentional reorienting throughout childhood and adolescence, the neural correlates underlying such changes in reorienting remain unclear. Herein, we used magnetoencephalography (MEG) to examine neural dynamics during a Posner attention-reorienting task in 80 healthy youth (6-14 years old). The MEG data were examined in the time-frequency domain and significant oscillatory responses were imaged in anatomical space. During the reorienting of attention, youth recruited a distributed network of regions in the fronto-parietal network, along with higher-order visual regions within the theta (3-7 Hz) and alpha-beta (10-24 Hz) spectral windows. Beyond the expected developmental improvements in behavioral performance, we found stronger theta oscillatory activity as a function of age across a network of prefrontal brain regions irrespective of condition, as well as more limited age- and validity-related effects for alpha-beta responses. Distinct brain-behavior associations between theta oscillations and attention-related symptomology were also uncovered across a network of brain regions. Taken together, these data are the first to demonstrate developmental effects in the spectrally-specific neural oscillations serving the flexible allocation of attention.

Transcranial stimulation of alpha oscillations modulates brain state dynamics in sustained attention

The brain operates an advanced complex system to support mental activities. Cognition is thought to emerge from dynamic states of the complex brain system, which are organized spatially through large-scale neural networks and temporally via neural synchrony. However, specific mechanisms underlying these processes remain obscure. Applying high-definition alpha-frequency transcranial alternating-current stimulation (HD α-tACS) in a continuous performance task (CPT) during functional resonance imaging (fMRI), we causally elucidate these major organizational architectures in a key cognitive operation-sustained attention. We demonstrated that α-tACS enhanced both electroencephalogram (EEG) alpha power and sustained attention, in a correlated fashion. Akin to temporal fluctuations inherent in sustained attention, our hidden Markov modeling (HMM) of fMRI timeseries uncovered several recurrent, dynamic brain states, which were organized through a few major neural networks and regulated by the alpha oscillation. Specifically, during sustain attention, α-tACS regulated the temporal dynamics of the brain states by suppressing a Task-Negative state (characterized by activation of the default mode network/DMN) and Distraction state (with activation of the ventral attention and visual networks). These findings thus linked dynamic states of major neural networks and alpha oscillations, providing important insights into systems-level mechanisms of attention. They also highlight the efficacy of non-invasive oscillatory neuromodulation in probing the functioning of the complex brain system and encourage future clinical applications to improve neural systems health and cognitive performance.

Visual evoked potentials waveform analysis to measure intracortical damage in a preclinical model of multiple sclerosis

Introduction

Visual evoked potentials (VEPs) are a non-invasive technique routinely used in clinical and preclinical practice. Discussion about inclusion of VEPs in McDonald criteria, used for Multiple Sclerosis (MS) diagnosis, increased the importance of VEP in MS preclinical models. While the interpretation of the N1 peak is recognized, less is known about the first and second positive VEP peaks, P1 and P2, and the implicit time of the different segments. Our hypothesis is that P2 latency delay describes intracortical neurophysiological dysfunction from the visual cortex to the other cortical areas.

Methods

In this work, we analyzed VEP traces that were included in our two recently published papers on Experimental Autoimmune Encephalomyelitis (EAE) mouse model. Compared with these previous publications other VEP peaks, P1 and P2, and the implicit time of components P1-N1, N1-P2 and P1-P2, were analyzed in blind.

Results

Latencies of P2, P1-P2, P1-N1 and N1-P2 were increased in all EAE mice, including group without N1 latency change delay at early time points. In particular, at 7 dpi the P2 latency delay change was significantly higher compared with N1 latency change delay. Moreover, new analysis of these VEP components under the influence of neurostimulation revealed a decrease in P2 delay in stimulated animals.

Discussion

P2 latency delay, P1-P2, P1-N1, and N1-P2 latency changes which reflect intracortical dysfunction, were consistently detected across all EAE groups before N1 change. Results underline the importance of analyzing all VEP components for a complete overview of the neurophysiological visual pathway dysfunction and treatment efficacy.

Using EEG to investigate the influence of boredom on prospective memory in top-down and bottom-up processing mechanisms for intelligent interaction

We aimed to investigate the alpha (α) activity in operators experiencing boredom while performing prolonged monitoring and prospective memory tasks using different processing mechanisms. Fifty-four participants underwent electroencephalography (EEG) and were found to have poorer prospective memory performance under top-down conditions. Further, α power and synchronisation were higher during bottom-up than in top-down processes, revealing an inhibition effect of the former. Significant differences in brain regions and hemispheres were identified to distinguish different cognitive processes in both information-processing mechanisms. Thus, people are likely to cope with boredom differently in terms of top-down and bottom-up processes. Specifically, a higher attention level was reported during top-down processing, to mitigate the negative influences of boredom. Overall, this study provides EEG evidence which suggests that prospective memory can be enhanced in top-down processing during prolonged monitoring tasks by increasing the salience of cues.